Pengfei Hou's repositories
cs61a_sp20
CS61A - Structure and Interpretation of Computer Programs, Spring 2020
app-template
Common conventions for building applications on the GeoDeepDive infrastructure
awesome-open-geoscience
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
badlands
Basin and Landscape Dynamics model
corebreakout
Segmentation and depth-alignment of geological core sample image columns via Mask-RCNN
CrudeAudacityMaps
"Geospatial mapping in python" webinar for Crude Audacity podcast
EarthSurface
Landscape evolution, deltaic systems, stratigraphy
Mines-ERDS
"Data Science: Earth Resources" graduate certificate at Colorado School of Mines
NolinearTimeSeriesAnalysis
The codes in the toolbox can be used to perform nonlinear time series analysis on single(or multi) channel data. This is done by mapping the single channel data to phase space representation using Taken's embedding theorem (compute_psv.m). The parameters - optimal delay and dimension are estimated using first minimum of MI (compute_tau.m) and FNN method (compute_dim) respectively. The recurrence network can be constructed from the phase space vector using ComputeRecurrenceNetwork_ANN.m or ComputeRecurrenceNetwork_fixedRR.m. The topology of the RN can be further analysed using graph theoreticl quantifiers (you need BCT toolbox for this). One can also compute the complexity-entrropy plane using get_mpr_complexity.m for which the ordinal patterns are computed using get_ordinal_pattern_dist.m (see the function descp for more details). Also, the tool box contains python codes to generate variety of uni(or multi) variate surrogate data.
nolitsa
A Python module implementing some standard algorithms used in nonlinear time series analysis
stRatstat
A R-based digitizer that is used to discretize hand-drawn stratigraphic sections/core logs into a numerical format for use in statistical analysis, visualization, or prediction of sedimentary strata.
trilium
Build your personal knowledge base with Trilium Notes
twitanalysis
Twitter analysis